How to Build Effective AI Agents to Process Millions of Requests
Last Updated on October 15, 2025 by Editorial Team
Author(s): Eivind Kjosbakken
Originally published on Towards AI.
Learn how to build production-ready systems using AI agents
AI agents have quickly become an effective way of using LLMs for problem-solving. Almost weekly, you see a new large AI research lab releasing LLMs with specific agentic capabilities. However, building an effective agent for production is a lot more complicated than it appears. An agent needs guardrails, specific workflows to follow, and proper error handling before being effective for production usage. In this article, I highlight what you need to think about before deploying your AI agent to production, and how to make an effective AI application using agents.
This article discusses the complexities of deploying AI agents in production environments. It emphasizes the importance of establishing guardrails, guiding agents through specific workflows, and implementing effective error handling to ensure the agents function properly. In addition, it highlights debugging agents by inspecting the input and output tokens, which helps identify and resolve issues faced during the process. Overall, the article provides a comprehensive guide for building and maintaining production-ready AI agents.
Read the full blog for free on Medium.
Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.
Published via Towards AI
Towards AI Academy
We Build Enterprise-Grade AI. We'll Teach You to Master It Too.
15 engineers. 100,000+ students. Towards AI Academy teaches what actually survives production.
Start free — no commitment:
→ 6-Day Agentic AI Engineering Email Guide — one practical lesson per day
→ Agents Architecture Cheatsheet — 3 years of architecture decisions in 6 pages
Our courses:
→ AI Engineering Certification — 90+ lessons from project selection to deployed product. The most comprehensive practical LLM course out there.
→ Agent Engineering Course — Hands on with production agent architectures, memory, routing, and eval frameworks — built from real enterprise engagements.
→ AI for Work — Understand, evaluate, and apply AI for complex work tasks.
Note: Article content contains the views of the contributing authors and not Towards AI.
Related posts
Recent Posts
